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# AI/ML Engineer

- **Company:** QTech US, Inc
- **Location:** Philadelphia, PA, United States (Remote available)
- **Experience:** Expert
- **Contract:** Temporary contract
- **Skills:** Artificial Intelligence, Amazon Web Services, Microsoft Azure, Cloud Computing, Continuous Integration, Data Cleansing, Graph Database, Python (Programming Language), Machine Learning, Natural Language Processing, Tensorflow, Azure Machine Learning, Software Engineering, SQL Databases, Enterprise Software Applications, Pytorch, Large Language Models, Snowflake, Apache Spark, Model Validation, Generative AI, Git, AI Platforms, Pyspark, Scikit Learn, Kubernetes, Information Technology, Deployment Automation, HuggingFace, Machine Learning Operations, Docker, Databricks
- **Published:** July 17, 2026
- **Apply:** https://www.dice.com/job-detail/75c4a524-c84b-47db-872e-727eb44b7eb8

## About the Role

Experience with MLflow or Kubeflow.
Experience with Apache Spark or PySpark.
Experience using Hugging Face Transformers.
Experience with Databricks and Snowflake.
Knowledge of Knowledge Graphs and Graph Databases.
Experience implementing enterprise MLOps solutions.
Bachelor's or Master's degree in Computer Science, Artificial Intelligence, Data Science, or a related field.
Best Regards

## Description

We are seeking an experienced Senior AI/ML Engineer to design, develop, and deploy enterprise-scale Artificial Intelligence and Machine Learning solutions. The ideal candidate will possess strong expertise in Python, TensorFlow, PyTorch, Scikit-learn, Large Language Models (LLMs), Generative AI, Retrieval-Augmented Generation (RAG), LangChain, Vector Databases, and cloud AI services on AWS or Azure. This role involves building scalable machine learning pipelines, deploying production-grade AI models, optimizing model performance, and collaborating with cross-functional teams to deliver innovative AI-driven solutions., Design, develop, and deploy AI/ML models for enterprise applications.
Build scalable machine learning pipelines and data preprocessing workflows.
Develop and optimize LLM, NLP, and Generative AI solutions.
Integrate AI models with cloud platforms and production systems.
Monitor model performance, retrain models, and improve model accuracy.
Build scalable inference pipelines and support production AI deployments.
Collaborate with Data Engineers, Data Scientists, and Software Development teams.
Participate in model evaluation, testing, documentation, and continuous improvement initiatives.
Follow MLOps best practices for model deployment, monitoring, and lifecycle management.
Required Skills:
Python
TensorFlow
PyTorch
Scikit-learn
Large Language Models (LLMs)
Generative AI
Retrieval-Augmented Generation (RAG)
LangChain
Vector Databases
AWS AI/ML Services or Azure AI/ML Services
SQL
Data Engineering Fundamentals
Docker
Kubernetes
Git
CI/CD
Machine Learning Pipelines
Data Preprocessing
Model Deployment
NLP


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